Bingzhe Wu

27 papers · 2019–2026 · 9 conferences · across top CS/AI conferences

Achievements

+11 more ↓

🐝 Cross-Pollinator (13) 🌍 Conference Polyglot (9) 🧭 Keyword Pioneer 🏃 Academic Marathon (6) 🌈 Renaissance Researcher (8)

🌈 Renaissance Researcher (8) 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (52) 🌱 Topic Pioneer 🏆 Grand Slam 🏆 Keyword Champion (2) 👑 Triple Crown 🗃️ Keyword Collector (98) ⚡ Prolific Year (11) 🚀 Conference Pioneer 💎 Century Club (26)

Conferences

AAAI (5) ICML (5) EMNLP (4) ICLR (3) NIPS (3) ACL (2) CVPR (2) IJCAI (2) ECCV (1)

Top co-authors

Yatao Bian (7) Peilin Zhao (7) Guangyu Sun (6) Shiwan Zhao (6) Liang Chen (5) Xiaolu Zhang (4) Changqing Zhang (4) Chaochao Chen (3) Qichao Wang (3) Zhirui Zhang (3)

Research topics

Differential Privacy (2) Privacy (1)

Keywords

uncertainty quantification (3) graph neural network (3) domain generalization (3) large language model (3) differential privacy (3) few-shot learning (2) confidence calibration (2) model robustness (2) membership attack (2) multimodal learning (2) predictive confidence (2) secure computation (1) stochastic gradient descent (1) density estimation (1) domain adaptation (1) privacy attack (1) federated learning (1) named entity recognition (1) post-training quantization (1) chain-of-thought reasoning (1)

Papers

CHAIRO: Contextual Hierarchical Analogical Induction and Reasoning Optimization for LLMs ACL 2026 NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction ICML 2025 Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model AAAI 2025 Measuring Diversity in Synthetic Datasets ICML 2025 IBCircuit: Towards Holistic Circuit Discovery with Information Bottleneck ICML 2025 Parameter-Efficient Fine-Tuning with Discrete Fourier Transform ICML 2024 VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models ICLR 2024 A Label Disambiguation-Based Multimodal Massive Multiple Instance Learning Approach for Immune Repertoire Classification AAAI 2024 Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization ICLR 2023 Federated Nearest Neighbor Machine Translation ICLR 2023 Density-Aware Prototypical Network for Few-Shot Relation Classification EMNLP 2023 Fairness-guided Few-shot Prompting for Large Language Models NIPS 2023 DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery – a Focus on Affinity Prediction Problems with Noise Annotations AAAI 2023 E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognition ACL 2023 Post-Training Quantization on Diffusion Models CVPR 2023 Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators EMNLP 2023 PsyCoT: Psychological Questionnaire as Powerful Chain-of-Thought for Personality Detection EMNLP 2023 RECAL: Sample-Relation Guided Confidence Calibration over Tabular Data EMNLP 2023 Calibrating Multimodal Learning ICML 2023 Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification IJCAI 2022 UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup NIPS 2022 S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search ECCV 2020 Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics AAAI 2020 Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection NIPS 2019 P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification CVPR 2019 G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification AAAI 2019 BAYHENN: Combining Bayesian Deep Learning and Homomorphic Encryption for Secure DNN Inference IJCAI 2019